Earnings management around mergers and acquisition deals - study in UK, France, Germany and The Netherlands
Name: Ayaz Durrani
Student number: 10885145
Thesis supervisor: Professor dr. Vincent O'Connell
Date: June 26 2017
Word count: 13444
MSc Accountancy & Control, specialization Accountancy Amsterdam Business School
Statement of Originality
This document is written by student Ayaz Durrani who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract
This study examines whether acquiring firms in the UK, France, Germany and The Netherlands use earnings management in order to increase their stock price prior to acquisition where stock is the primary payment method. Furthermore the long-term post-acquisition performance of those acquiring firms is analyzed. The accruals were calculated by using the modified Jones model. I find that firms’ managers engage in upward earnings management in stock financed deals in order to boost their stock prices. For the estimations of long-term post-acquisition performance I use the buy-and-hold return (BHAR) estimation method. The BHAR estimations show that the acquiring firms suffer a decrease in the long-term (3 years after the deal) post-performance when the deal is financed by stocks. Cash-financed deals perform better in the post-acquisition performance. These findings are in line with previous studies of Erikson & Wang (1991) and Botsari & Meeks (2008). I contribute to the literature by examining the existence of earnings management and the long-term post-deal performance of mergers and acquisitions.
Table of content
Abstract 3
1. Introduction & research question 6
2. Literature review & hypothesis development 9
2.1 Earnings management 9
2.2. Motives of earnings management 10
2.3 Earnings management around Mergers and Acquisitions 12
2.4 Measurements of earnings management 14
2.5. Long-term post performance on M&A deals 15
2.5.1. Buy and hold abnormal return (BHAR) 16
2.6 Hypothesis development 17
3. Research method and Data 18
3.1 Data 18
3.2 Research method 22
3.2.1 Probit analysis 25
3.2.2 Buy-and-hold Abnormal Return post-performance M&A Deals 27
3.3 Descriptive statistics 29 4. Results 31 4.1 Hypothesis 1 31 4.1.1. Main results 31 4.2. Hypothesis 2 33 4.2.1. Main results 33 4.3 Sensitivity analysis 41
4.3.1 Sensitivity analysis H1 41
4.3.2 Sensitivity analysis H2 43
5. Conclusions, limitations and suggestions for further research 49
5.1 Conclusions 49
5.2 Limitations 50
5.3 Suggestions for further research 51
6. References 52
6 1. Introduction & research question
Due to the globalization in the capital markets, mergers and acquisitions (M&A) have become one of the most used tools for firms to expand their position in the market. Higgins (pp. 44, 2013) defines mergers as events which are associated with the creation and redistribution of wealth. In other words, mergers and acquisitions deals have an influence on the whole market structure (Andrade et al., 2001). The fast growing financial world is one of the main reason for firms’ managers to engage in earnings management. So managers actually manipulate the earnings income in order to boost the firms’ stock price in the market. In this thesis I will show that managers engage in upwards accruals earnings management prior to a (stock financed) mergers and acquisitions deal. How the firms perform in the years following the acquisition, will also be studied. The main goal of a firm is to make profit and to have the highest value for their stocks. This gains trust from investors/owners as their wealth will increase too. Ideally, the market could anticipate the existence of earnings management and its effect on the years after the M&A deal. Unfortunately, that is not the case since managers have access to private information which is not available for other parties. This phenomena is known as ‘information asymmetry’.
In order to engage in an M&A deal the management of both parties come together and agree on a purchase price. So when this transaction is completed, the shareholders of the target firm receive a number of shares of the acquiring firm for each of their own shares. The very first step in a stock for stock mergers and acquisition deal is that both parties agree on a purchase price. This is determined by the price of the acquiring firm stock at the time when the agreement is reached. In this whole process, one could say the higher the price of the stock of the acquiring firm on the agreement date, the less number of shares are need to purchase the firm (Erickson & Wang, pp. 27, 1999).
When both parties are agreed on the price, then the acquiring firm takes over the other firm and it becomes one firm operating through the same name as the acquiring firm. In order to acquire the assets of the target firm, all shareholders should agree on the deal. Once it is decided that an M&A deal is paid by stocks, the shareholders of the target firm get a notice. In this notice the shareholders have to respond whether they will accept or decline the offer made by the acquiring firm (Erickson & Wang, 1999).
7 As mentioned above an M&A deal can be paid by stock but also by cash or a mix of cash and stocks. Stock financed M&A brings the most benefits to the firms’ managers as these stocks are overvalued. When a deal is completed, the acquiring firm will give their stocks for each stock of the target firm. So the higher the ‘’artificially’’ overvalued stock value, the less stocks need to be exchanged by the acquiring firm (Erickson & Wang, 1999).
In academia, there are a large number of studies available regarding the M&A activities of firms by many academics, regulators and auditors. In this thesis, I will mainly focus on the earnings management around M&A deals. The reason for this approach is that there is a wide range of literature available about earnings management related to M&A. Due to the accounting scandals, the reliability of financial information has been questioned. The quality of earnings is becoming a more discussed topic due to the scandals.
There is a broad existing literature available regarding the role of earnings management during M&A activities. Studies in the US and UK have shown that earnings management does play a role in the M&A deals. One of the very first studies about earnings management before M&A deals was done in the US by Erickson & Wang (1999). But there are a few studies which focus on the other European countries. In this thesis I will investigate the effect that earnings management has on mergers and acquisitions deals in the major countries in the EU; UK, France, Germany and The Netherlands. The period under investigation will be between 2000 and 2016, so I will show what effect the earnings management had on the M&A deals in that period of time. Also I will analyze how the acquiring firms perform in the years following the deal.
In the research method part of this thesis I have analyzed a sample of 4373 M&A deals in order to test whether accruals earnings management was present one year preceding the deal. Also I analyzed the long-term post-acquisition return performance of those acquiring firms. My findings were consistent with previous studies like Erikson & Wang (1999), Louis (2004) and Botsari & Meeks (2008). These studies suggested that acquiring firms have anticipated the M&A deals. There are a few things which makes this topic an interesting question. First of all, this will be the first study focusing on the M&A activities in the major countries in Europe Furthermore it will add meaningful information to the existing literature and relevant suggestions for future research. The research question during my thesis period will be as follows;
8 What is the influence of earnings management on the M&A deals in the UK, France, Germany and The Netherlands during the period 2000-2016?
The main purpose of this thesis is to understand the relationship between earnings management and mergers and acquisitions. After testing the hypotheses, I will be able to show whether the M&A deal was a success or a failure. By testing the existence of earnings management and long-term post-acquisition return performance, I want to add explanatory power to the knowledge of earnings management.
The thesis is divided into five main parts. After the introduction, the second part, Literature Review, will discuss the previous studies about earnings management around M&A deals and the long-term post performance. In the third part, Data and Research Method, I will discuss the samples used in this study, the resources I have used, the methodology and how I finally collected the data to test my hypothesis. The fourth part, Results, will include the analysis of the tests and the final results. In the fifth and last part, Conclusion, I will discuss the main conclusions, limitations and I will give suggestions for further research.
9 2. Literature review & hypothesis development
This research is related to prior studies which investigate whether managers in acquiring firms engage in upwards earnings management regarding mergers and acquisitions (hereafter M&A). Also I will discuss some previous studies which show the effect that earnings management has on M&A.
In order to understand the background of earnings management and the implications of this accounting choice it is important to have some knowledge about the whole concept of earnings management. It is essential to define earnings management so one is able to understand its boundaries.
2.1 Earnings management
There are many definitions for earnings management and the motives behind earnings management. Healy and Wahlen (1999, p.368) define earnings management as follows:
‘’Earnings management means when managers use judgment in the financial reports and to structure transactions to adjust the financial reports. The objective is to mislead the stakeholders about the financial performance of the company and to affect the contractual outcomes that depend on the financial reported numbers’’ (Healy and Wahlen, p.368)
Another definition for earnings management comes from Pungaliya & Vijh (2009). Earnings management are inflating or deflating accruals and concern within reporting standards such as GAAP. The objective of earnings management is to obtain private gain through manipulating the earnings income. Earnings reflect the financial performance of a company. Data of earnings is then used to predict the future financial performances. Thus earnings management can lead to a negative earnings quality.
Deangelo (1995) was one of the earliest studies on earnings management. In his paper, it is explained that firms manipulate the financial reporting by increasing the accruals income. On the other hand, the study of Dechow et al. (1996) shows that firms which engage in earnings management in their first year, have a worse financial performance in the following years. It is also argued in literature by Beneish (1999) that if firms increase their accruals, the firms do not have
10 any other options left in the future to manipulate the earnings. So it is evident that managers of those firms may commit fraud again when they have to face reversals of those earnings.
There are studies which show that managers have incentives to engage in earnings management. The reason for this is that managers do this for contractual incentives (i.e. bonuses) in order for private gain. The motives behind earnings management will be discussed during the literature review. Earnings management also occurs when firms try to sell their shares. This leads to a decrease in the earnings quality because these earnings do not reflect the real performance of a company.
To highlight the point made earlier about the fact that the management of the company uses judgment in financial statements which consist of both cost and benefits. The first component cost, could be a misallocation of a resource which arises from the fact that a company engages in earnings management. The other component, benefits, are improvements in the communication of value relevant information to the external parties such as stakeholders. To structure the background of earnings management, it is essential to know the motives behind earnings management.
2.2. Motives of earnings management
Identifying the situations in which management motives to engage in upwards earnings management are strong, is one of the approaches to test for earnings management. There are several incentives, supported by literature, which show why firms engage in earnings management. First the management compensation contracts can lead to earnings management. There are a lot of studies which examined whether managers engage in earnings management due to their compensation contract. Researchers such as Guidry et al. (1998) showed that division managers of a large firm are more likely not to change the income when the target of earnings in their compensation contract will not be achieved and when managers are permitted to earn the maximum bonus. Guidry et al. (1998) showed that firms which are entitled to maximum bonus plans are more likely to engage in earnings management in comparison to firms which have no maximum bonus plans. Compensation contracts encourage some firms to engage in earnings management in order to maximize their bonus rewards. However, there is insufficient evidence that earnings management for bonus plans has an influence on the stock prices of firms.
11 Secondly, accounting data is used to monitor the contracting between the firm and its external parties such as stakeholders. It is important to align the incentives of the management and the stakeholders. Contracts should prevent that managers’ actions would lead to benefits at the expense of others. There is a large amount of literature regarding contracting and the role of firms’ managers in earnings management.
At the third place, accounting information is used as a tool by investors and analysts in order to create value for stocks. Managers have strong incentives to manipulate the income to have an effect on the stock price. Firms always need to beat the forecast of analysts, especially when an analyst projected a bad expectations of the firm. Firms will create an impression that they are performing well and increase the confidence of the market. According to some other studies (Healy and Wahlen, 1999; Defond, 1998) firms will engage in earnings management if they are unable to meet their liabilities. By engaging in earnings management, they will try to gain capital from external parties, such as banks. In case of a loss or in a case of meeting certain requirements in a bonus plan, firms are then eager to manipulate their earnings. According to Healy and Wahlen (1999) managers are more encouraged to engage in earnings management if there is a strong correlation between the stock price and bonus plan incentives.
Actually, earnings management does not only occur in mergers and acquisitions. Earnings management also occurs in initial public offerings and seasoned equity offerings. There are a lot of previous studies which showed the relationship between earnings management and SEO and IPO. Teoh et al. (1998) show the relation between earnings management and the long-term SEO performance. They came to the conclusion that firms which engage in earnings management have a decrease in the long-term post-merger performance, lower stock return and a lower net income. Their sample consisted of 1265 SEO issuers during the period 1976-1989. Also in this thesis, the long-term post performance of firms will be tested.
Cohen and Zarowin (2010) find in their study that SEO firms which engaged in earnings management faced the consequences which was the decrease in performance. Their sample consisted of 1551 SEO offers between 1987-2006.
12 Earnings management also occurs in IPO’s. In a Dutch study, Roosenboom et al (2003) shows that firms which engage in higher levels of earnings management, showed a lower stock return after the IPO’s. Their sample consisted of 64 IPO’s during 1984-1994.
In a French study, Still et al. (2013) find that firms which manipulated their earnings, measured with the Modified Jones model, have lower returns and a decrease in financial performance in the years following the IPO’s. Their sample consists of 139 IPO’s during 1999-2007.
Bao (2013) showed that US IPO firms engaged in earnings management to report better looking financial statements. This study consists of 1014 IPO firms in the US during 1990-2007.
In the next section, earnings management around mergers and acquisitions will be discussed. 2.3 Earnings management around Mergers and Acquisitions
Earnings management around mergers and acquisitions is tested before in the academia. According to Degeorge et al. (1999) and Burgstahler and Eames (2006), most research is done before seasoned equity offerings and IPOs. There are some studies which have examined the role earnings management plays around mergers and acquisitions. Acquiring firms show a lot of interest in other firms when their stock price exceeds the fair value. Managers of a firm know that when the stock price is higher they will lower the cost of investing. Acquiring firms thus pay more with stock than with cash especially when their (acquiring firm) stock price is overvalued.
The very first study for earnings management around mergers and acquisitions was done in the US by Erickson & Wang in 1999. In a sample of 119 firms in the period between 1985 and 1990 there was sufficient evidence found that 55 US firms showed abnormal accruals before mergers and acquisitions deals (stock for stock deal). These firms used earnings management in order to create more firm value. There was no evidence found for the other 64 cash acquisitions. So they have found evidence that acquiring firms engage in upwards earnings management in order to increase their stock price.
Other researchers such as Botsari & Meeks have analyzed 42 UK publicly traded firms which have undertaken stock-for-stock acquisitions. Their results suggest that acquiring firms use earnings management as a tool to manipulate the earnings immediately in the year prior to the announcement of the acquisition. Botsari & Meeks argue that their results lead to the phenomena of signaling
13 (2008, pp. 664). Signaling occurs when a stock offer is used as an indicator of earnings management when the stock price is overvalued.
A study of Louis (2004) had different results and conclusion. Their sample consisted of 373 deals in the US in the period 1992-2000. Their results showed that stock for stock M&A reveal that firms engage in earnings management and that cash payments are not a part of earnings management. Heron and Lie (2002) disagree with Eriksson and Wang (1999). They find that the acquiring firms always prefer to pay their acquisition with stocks, which are most of the times overvalued. In cases when the stocks are below the market price then the acquiring firms will pay with cash. The stocks are below the market price, when the firm is not performing well. In their sample of 859 deals in the US market during 1985-1997 they find that there is no sign of earnings management preceding the deal. Heron and Lie (2002) have a different conclusion than Erickson and Wang (1999). A possible explanation is that they have used a different sample and methods to measure the accruals earnings management.
Recent research of Higgins (2013) examined Japanese M&A deals on the Tokyo Stock Exchange. The examination focuses on long-term accruals because in Japan, earnings management is often done via long-term accruals. The findings of this paper show that M&A deals in Japan report abnormal returns. These findings are consistent with the incentive that in stock for stock mergers, the managers engage in upwards earnings management to lower the cost of financing (Higgins, 2013).
A more recent study of Vasilescu and Meeks (2016) investigated whether earnings management plays a role in corporate diversification, in a sample of 229 UK publicly listed target firms in the period 1990-2008. They report on industrial and geographic diversification. Their analysis shows that industrial diversification mitigates earnings management by UK targets prior to a merger and acquisition deal.
14 2.4 Measurements of earnings management
One widely accepted definition is that earnings are the sum of accruals and operating cash flows of a firm in a period. According to the literature Dechow & Schrand (2004) assume that fluctuations in cash are observed as result of daily activities. In literature it is argued that deals paid with cash are harder to manipulate than deals which are paid by stocks. But at the same time accruals are an estimation thus are more uncertain and less like to be reliable than cash flows. Accruals can be divided in two types; discretionary and non-discretionary accrual. The main difference between these two types is that the non-discretionary accruals can be measured and verified. The other type, discretionary accruals, are harder to detect and to measure.
However there is a debate where researchers argue which model is more suitable for the measurement of accruals. Botsari & Meeks (2007) used both models in their study, discretionary and non-discretionary accruals, to do their analysis. Both models confirmed that acquiring firms engaged in upwards earnings management prior to the M&A deal. But noticeably they found more significant evidence when they used the cash flow method.
According to the study of Watts & Zimmerman (1990) they assume that accruals-based model are more attractive because the accruals are combined into a particular number which reflects the net effect of numerous accounting policies. They suggest that accruals reduce the problems associated with the incapability to measure the effect of the accounting choices based on the earnings. Dechow et al. (1995) investigated the ability of alternative models to detect earnings management. The results of this research show that the models to detect earnings management produce reasonable evidence. Dechow et al. (1995) give a brief explanation of various models to detect earnings management. The authors conclude that a modified version of the Jones (1991) give the most meaningful tests of earnings management.
However, Vladu (2014) mentioned in his paper that the accruals based model is widely used in studies around earnings management. The models to estimate the earnings management are based upon models used in previous studies. Ideally, there should be one specific global model which detects accruals earnings management. Most of the models tested are based upon the (Modified) Jones model.
15 So the most used models to detect earnings management are the standard and modified Jones model. Because of the fact that modified Jones model includes receivable variance, it gives more meaningful results than the standard Jones model. So splitting the accruals (non-discretionary and discretionary) has an important role. Beside this, studies of Kothari and Watts (1996) showed that the modified and the standard Jones model can provide consistent estimations of the accruals. The accruals are defined as non-cash flow parts of the accounts. These elements are easily manipulated by the management of the firm (Jones, 2011). A few examples of these elements are; inventory, payables and receivables. The manipulation with inventory could occur when the inventory is overvalued, by including fixed overhead cost, instead of charging the inventory at cost basis. Manipulation of amortization is also a tool to manipulate earnings. When firms change the useful life of an asset and therefore the amortization expenses, they are then actually engaging in earnings management.
According to Jones (2011) the total accruals represent the discretionary and the non-discretionary accruals. In his study, it states that manager are only able to manipulate the discretionary accruals. Discretionary accruals have more uncertainty than non-discretionary accruals. So the accruals earnings management is a whole process where managers try to manipulate the earnings income during a year in order to gain confidence from the investors.
In this thesis, I will use the modified Jones model. The dependent variable of this research will be the total accruals. The non-discretionary accruals act as the independent variables. The discretionary component is the regression’s residual. In chapter 3 the Jones model will be discussed in detail.
2.5. Long-term post performance on M&A deals
In above paragraphs I have discussed earnings management (EM) in general, the motives behind earnings management, EM around M&A deals and how to measure the EM. Once a M&A deal is done, the firms’ main goal is that it should be profitable. But not always is this the case. If the firm engages in upward EM preceding the M&A deal. In this thesis, as mentioned before, the long-term performance of acquiring firms will be analyzed. However some studies in the past argue that the payment method plays a crucial role in detecting EM. In order to test for this, the performance of the acquiring firms using the long-term abnormal returns (BHAR model) will be tested.
16 2.5.1. Buy and hold abnormal return (BHAR)
In this section I will discuss the previous studies regarding earnings management and the long-term post performance of acquiring firms. A tool to measure the post-performance of firms is to calculate the buy-and-hold abnormal returns of firms. Abnormal return are used to describe the returns generated by a security/portfolio over a certain period and is different from the expected rate of return (Investopedia). As mentioned before, firms want to have profitable M&A deals but do not always succeed in this process.
Louis (2004) has done a study including 373 deals completed between 1992-2000 in the US. The most of these deals, 263, are 100% stock financed. He reports a negative long-term post-merger performance. Especially for the stock financed deals this is statistically significant following the years when the deal is done.
Mitches & Stafford have analyzed the BHAR of 4911 US firms during 1958-1993. In their study the tested the performance of the firm’s 3 years after the deal. They came to the conclusion that the firms underperformed in comparison with firms operating in the same branch. They explicitly discuss that firms which are financed by stock have a weaker performance than the firms which are financed by cash.
Agrawal et al. (1992) have done a study in the US and their sample consists of 937 M&A deals completed during 1955-1987. They find support that there is a decrease in long-term performance of those firms. In a period of 5 year after the deal, the firms have made a loss of around 10%. Overall the long-term performance is a debatable topic and has many divisions. There are many discussions going on in the research area on how to measure the long-term post performance of firms. However there is still no one globally accepted model which is used to measure the post deal performance, because there are many options to measure this. One of them is calculating the BHAR of the firms in the years following the M&A deal.
17 2.6 Hypothesis development
Globalization in capital markets led to more cross-border transactions which were a part of mergers and acquisitions. When two parties, the acquiring firm and the target firm agree on an M&A deal, the acquiring firm needs to decide which method of payment to choose. Some firms do have a lot of cash, but they do not pay only in cash. As is explained in the first paragraph, cash payments for mergers and acquisitions deals do not often relate to earnings management. Acquiring firms would like to limit their cash payment, because they see more earnings management potential in stock-for-stock deals. Especially when the stock price of the firm is overvalued, acquiring firms feel more attracted to engage in a stock for stock deal. The possibility of a stock deal gives more benefits and a better deal ratio (amount of stocks of the acquiring firm versus the stock of the acquired firm). Having mentioned the above, I formulate my first hypothesis as follow:
H1: Acquiring firms in the UK, France, Germany and The Netherlands engage in upwards earnings management one fiscal year prior to an acquisition
Next to the question whether acquiring firms engage in earnings management, it is relevant to know whether the deal was a success or a failure. In order to give an answer to this, I will analyze the long-term post-deal performance of the acquiring firm. It is expected in the literature review that firms which engage in earnings management and have made stock financed deals, the long-term post performance is negative. Building on the literature part, I will formulate my second hypothesis as follow:
H2: The long-term post-deal performance of the acquiring firms in stock financed M&A deals is weaker when the acquiring firms engaged in upwards earnings management.
My research question for this thesis will be as follows;
What is the influence of earnings management on the M&A deals in the European Union during the period 2000-2016?
18 3. Research method and Data
3.1 Data
This dissertation aims to contribute to the existing literature regarding accruals earnings management around mergers and takeovers in the UK, France, Germany and The Netherlands. Previous studies which focused on earnings management around merger and takeover are done by Erikson & Wang (1999) (US) and Botsari & Meeks (2008) (UK). In previous studies the emphasis was only on the existence of earnings management around the mergers and takeover. In this thesis, the performance of the firms after the deal will also be analyzed.
In order to form the sample, the data is collected through the combination of multiple databases such as the database of Thomson Financials SDC and the downloading of the M&A deals from the database of Zephyr and Amadeus. In Amadeus I will look for all firms in the countries (UK, France, Germany and The Netherlands) that were engaged in M&A deals in the period between 2000 and 2015. These firms will be only the consolidated firms, so there is one reporting standards for all the firms.
From the database of Zephyr the completed deals will be collected. In this database more information regarding the acquiring firm and target firm will be collected. To show the differences between the amount of cash, stock or a combination of both payment methods, this thesis will include cash and stock for stock mergers and acquisition deals. A deal can be paid by stocks, cash or a combination of both. In this thesis I will include the mix payments as well, since only 11% of the sample is paid by 100% stocks. But the emphasis of this study is more on the stock for stock M&A deals. All cross border mergers will be excluded in this paper, where the target firm is a foreign firm (i.e. outside the European Union). There were firms with more than one (completed) deal, so only the deal with the earliest announcement date is included in the sample.
19 In order to include a acquiring firm in the sample, I will use the criteria as in the paper by Botsari & Meeks (2008). The only difference is that my sample will consist of acquiring firms in some major European countries. The criteria which I will apply for my sample are as follows;
1. The M&A deal must be announced within the period I will investigate, 01-01-2000 till 31-12-2015
2. The acquiring firm must have a majority interest (more than 50% interest) in the acquired firm or end up a majority interest at the end of the deal.
3. There must be sufficient data available regarding accounting information to estimate the discretionary accruals and the post-performance of the acquiring firms
4. The acquiring firm must be operating in the four countries (UK, France, Germany and The Netherlands). No restrictions for the target firm
5. The transaction must be either stock for stock swap or cash
6. The Deal value of the merger/takeover is at least $ 1 million dollars
7. Only the very first merger/takeover is included for the acquiring firm. Since there are firms which made more than 1 deal in a year.
8. Acquiring firms from the financial sector are excluded because of their complexity regarding disclosure requirements (SIC between 6000-6999)
There is a discussion about which date to choose for the M&A deal. Since the time between the announcement date and effective date of the merger/takeover is several months, in this case the announcement data is chosen as effective date. This approach is also supported by several previous studies (Botsari & Meeks, 2008; Louis, 2004). After applying the above criteria, there were firms which lacked accounting information and thus were excluded from the final sample. To reduce the effect of outliers, the respective variables in this case were winsorized at 1 % and 99%. In order to apply the appropriate criteria to form my sample, I have looked at previous studies of Botsari & Meeks (2008) and Louis (2004).
After applying all the criteria, a total of 42,357 mergers and acquisitions deal were collected. After merging it with the other data, there were a total of 2560 acquiring firms and in total were 4373
20 acquisitions. These acquisitions are done in the following countries; the UK, France, Germany and The Netherlands. A percentage of 60% of the M&A deals had the same 2-digit SIC code and around 45% had the same 3-digit SIC code. That means that half of the sample is between target and acquiring firms which operate in different industries. Over 55% of the mergers and takeover include acquiring firms and target firms which are operating in the same country.
In the following table 1 the data distribution is provided in panel A. In panel B an overview of the payment method and respective years is given and in panel C the overview of the merger and takeovers per country. It is important to mention that in panel C, the amount of deals in the UK is the highest since the capital market in this country is the biggest. Also one of the very first study regarding earnings management around M&A deals was in the UK.
Panel A shows the distribution of the data by 1-digit SIC. SIC codes between 20 and29: food textile, chemicals etc. SIC codes between 30 and 39: leather, metal, electronic etc. SIC codes between 70 and 79: personal, business, hs, camps etc. SIC codes between 80 and 89: health, legal, social etc.
21 Panel B shows the distribution of the data per year of the deal announcement. The maximum year of the sample is 2015, because for 2016 not all accounting information was available. Therefore the decision to only take 2015 as last year for the announcement data. The third column of Panel B shows the difference ‘Period distribution’ in percentage compared with previous year.
Panel C shows the amount of M&A deal in the respective country which were financed with stock. Around 45% of the sample was paid by cash and other by stock or mixed payment. Only 4 countries are included in the sample as these are the major EU countries where M&A deals mainly occurs.
22 3.2 Research method
The research method I will apply is as follow; I will look at the level of discretionary accruals of the firms. More specifically, I will make a comparison of the discretionary accruals (one year before the deal) In order to have comparable data, there is criteria for the acquirers that is must be of same size, financial performance etc. In the most ideal situation, the total assets of one firm in relation to another should not be greater than 50%. The firms in the sample must be unique, with other words the firm should not be an acquiring firm in a different year of the sample.
There are various models to estimate the accruals so the researchers can analyze whether firms engage in earnings management. One of the models is the Jones model. This is a widely used model in previous studies around mergers and acquisition deals. Jones (1991) was the first to introduce an expectation model that takes into account the changes in economic circumstances of the firm, but in its sectional variation as introduced by DeFond and Jiambalvo (1994). This cross-sectional estimation is about constructing industry-event period matches for each firm, estimating regression for each year/industry combination to generate industry/year specific estimates (Botsari & Meeks, pp.637, 2008) The cross sectional estimation of the standard Jones model (1991) is as follow:
The above estimation is explained as follows;
23 Where, for firm i in year t:
TotAcc = change in non-cash current assets - the change in net income and cash flow from operations;
ΔREV = revenues in year t - revenues in year t-1;
ΔREC = accounts receivable in year t - revenues in year t-1; PPE = gross property plant and equipment;
TAit-1 = Total assets at t-1.
It is also essential to compute the non-discretionary accruals from the regression. This estimation will be done by using the following model;
(Model 2) The next step is to estimate the discretionary accruals also shows as DISCACC. The following model is used in practice to calculate if firms use accruals earnings management;
(Model 3) (Botsari & Meeks, pp.637, 2008).
In order to detect earnings management, it is important to estimate the discretionary accruals. This will be done with the same estimation used in the research of Botsari & Meeks (2008).
24 The empirical model I will use will be the modified Jones model. One of the implicit assumptions of the Jones model is that revenues are non-discretionary. But if earnings are managed via discretionary revenues, then this model can remove the part of the managed earnings from the discretionary accruals. In response to this implication, Dechow et al. (1995) introduced a modified version of the model. This model is identical to the standard Jones model to estimate the discretionary accruals. The only difference is that the change in accounts receivable (REC) is subtracted from REV at the second stage.
This modified Jones model assumes that all changes made in the credit sales in the event period result from earnings management. It is thus easier to manage earnings by exercising discretion of the recognition of revenue on credit sales rather than manage earnings by exercising discretion via cash sales. Research shows that through research that the modified Jones model is more powerful and superior in estimating discretionary accruals compared to the standard Jones model (Dechow et al., 2005).
The data I will use refers to M&A deals in Europe as whole. So I have looked at data of M&A deals which consist all countries which are a member of the European Union.
In comparison with other studies in the US and UK such as the one of Higgins (2013), Botsari & Meeks (2008) and Erickson & Wang (1999) which analysed only listed acquiring firms, I will look at both listed and non-listed firms. The researchers mentioned above have all found evidence that acquiring firms engage in upwards earnings management. This paper will focus more on the European M&A deals and test whether acquiring firms also used earnings management during the period after the global crisis in 2008 till 2016. So I will investigate whether those firms used accounting techniques in order to engage in upwards earnings management prior to the acquisition. The discretionary accruals will be calculated through the modified Jones model for each acquiring firms and the matched firm prior to the M&A deal.
25 3.2.1 Probit analysis
My first hypothesis is as follows;
H1: Acquiring firms in the UK, Germany, France and The Netherlands engage in upwards accruals earnings management one fiscal year prior to the acquisition
To test this a probit model will be used to test for accruals earnings management in the four countries. A probit model is a model where there are only two values for the dependent variable. In this model I will test if firms in the four countries engaged in AEM preceding the deal. The aim is to test if firms managers anticipated the stock financed deal and engaged in upward earnings management The test will be done by using the following probit regression;
DStock= β0 + β1EM + β2𝑀𝑇𝐵𝑖𝑡−1 + β3𝑅𝑂𝐴𝑖𝑡−1 + β4𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒𝑖𝑡−1
+ β5𝐷𝑒𝑎𝑙𝑆𝑖𝑧𝑒𝑖𝑡 + β6𝐶𝑟𝑜𝑠𝑠𝐵𝑜𝑟𝑑𝑒𝑟𝑖𝑡 + β7𝐶𝑟𝑜𝑠𝑠𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦𝑖𝑡 + 𝜏𝑖𝑡
Model (4)Where, for firm i in year t:
DStock = Dummy variable, 1 if it is a merger/takeover in year t, 0 otherwise
EM = Earnings management
MTB = Market to Book (Market value/Book value Equity) ROA = Return on Assets (Net income/total assets)
Leverage = Leverage, (Total liabilities/Total assets) Dealsize = Value of the deal/Total assets of the firm
CrossBorder = Dummy variable, 1 if it is a cross-border deal, 0 otherwise CrossIndustry = Dummy variable, 1 if it is a cross-industry deal, 0 otherwise
26 Since the aim of this study is to show how accruals earnings management occur in M&A deals, the focus will be mainly on deals which are paid by stock. However 50% of the deal are paid by cash. In order to show the difference between the stock and cash financed deals I will test EM for cash financed deals too. As widely discussed in the literature the expectation of earnings management, the probability that EM occurs in cash financed deal is low. But to show the difference between the two payment methods, I will do another regression which is a replica of the regression above, only the dependent variable is now ‘DCash’ (Dummy variable, 1 if deal is paid by cash 0 otherwise) and is as follows;
DCash= β0 + β1EM + β2𝑀𝑇𝐵𝑖𝑡−1 + β3𝑅𝑂𝐴𝑖𝑡−1 + β4𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒𝑖𝑡−1 +
β5𝐷𝑒𝑎𝑙𝑆𝑖𝑧𝑒𝑖𝑡 + β6𝐶𝑟𝑜𝑠𝑠𝐵𝑜𝑟𝑑𝑒𝑟𝑖𝑡 + β7𝐶𝑟𝑜𝑠𝑠𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦𝑖𝑡 + 𝜏𝑖𝑡 (model 5)
Where, for firm i in year t:
DCash = Dummy variable, 1 if it is a (cash financed) merger/takeover in year t, 0 otherwise
EM = Earnings management
MTB = Market to Book (Market value/Book value Equity) ROA = Return on Assets (Net income/total assets)
Leverage = Leverage, (Total liabilities/Total assets) Dealsize = Value of the deal/Total assets of the firm
CrossBorder = Dummy variable, 1 if it is a cross-border deal, 0 otherwise CrossIndustry = Dummy variable, 1 if it is a cross-industry deal, 0 otherwise
27 3.2.2 Buy-and-hold Abnormal Return post-performance M&A Deals
In this section I will discuss which model I will use to test my second hypothesis which is as follows;
H2: The long-term post-performance of acquiring firms in the UK, Germany, France and The Netherlands is weaker when they engaged in upwards accruals earnings management preceding the acquisition
Previous studies like the one of Louis (2004) opted for the buy-and-hold abnormal returns model, also called the BHAR model. This model is used by many researchers in the past to analyse the post-deal performance of the firms. In order to get solid results from this BHAR model, one needs analysis over a longer period, because according to Louis (2004) the abnormal performance could occur in the first year but even in the third year. So to avoid the fact that one takes conclusions too soon, it is essential to do an analysis for a longer period of time.
The BHAR model is defined in the literature as the expected return on a buy-and-hold investment at a specific time. First, you have to estimate the expected return on a buy-and-hold investment. Once this is done for the 3 year period after the deal then you should minus that amount with the return on a buy-and-hold investment according to the benchmark.
The buy-and-hold abnormal return model is defined as follows;
28 Where,
Ri,t = Weekly return of firm i in week t;
Rbenchmark,t = Weekly return of the market index of country i in week t.
However there are some concerns regarding using this BHAR model. The issue is that the model expects that the event’s abnormal returns are independent. But there are also events which are not random but there are some which could overlap other observations for the period which BHAR is calculated. In order to avoid any problems, such as positive cross-correlation, I have clustered the standard errors of the regression at year and country year level.
The following BHAR regression is as follow;
𝐵�𝐻�𝐴�𝑅� = 𝛼�0 + 𝛼�1𝐷�𝑆�𝑡�𝑜�𝑐�𝑘�𝑖� + 𝛼�2𝐿�𝑜�𝑔�𝑇�𝑜�𝑡�𝐴�𝑠�𝑠�𝑒�𝑡�𝑠�𝑖� + 𝛼�3𝐿�𝑒�𝑣�𝑒�𝑟�𝑎�𝑔�𝑒�𝑖�
+ 𝛼�4𝑅�𝑂�𝐴�𝑖�
+
𝛼�5𝐷�𝑒�𝑎�𝑙�𝑆�𝑖�𝑧�𝑒�𝑖� + 𝛼�6𝐶�𝑟�𝑜�𝑠�𝑠�𝐵�𝑜�𝑟�𝑑�𝑒�𝑟�𝑖� + 𝛼�7𝐶�𝑟�𝑜�𝑠�𝑠�𝐼�𝑛�𝑑�𝑢�𝑠�𝑡�𝑟�𝑦�𝑖�+
𝛼�8𝑃�𝑢�𝑏�𝑙�𝑖�𝑐�𝑖� + 𝜀�𝑖�
Where, for firm i
BHAR = Buy-and-hold abnormal returns;
DStock = Dummy variable, 1 if it is a 100% stock-financed acquisition, 0 otherwise; LogTotAssets = Logarithm of Total Assets;
Leverage = Leverage (Total Debt / Total Assets);
ROA = Return on Assets (Net Income / Total Assets);
DealSize = Relative Deal Size (Value of Transaction / Total Assetst-1); CrossBorder = Dummy variable, 1 if it is a cross-border acquisition, 0 otherwise; CrossIndustry = Dummy variable, 1 if it is a cross-industry acquisition, 0 otherwise;
29 Public = Dummy variable, represent a Public target firm if 1, and 0 otherwise;
ε = Error term.
As mentioned before the BHAR model is often used in the literature to analyze the long-term post-performance of firms. In order to get solid results from this test, I have winsorized all above variables at 1% and 99% to avoid any outliers.
3.3 Descriptive statistics
In this section I will present an overview of my full sample which consist of 4373 mergers and acquisition deals in the UK, France, Germany and The Netherlands over the period January 2000 till December 2015. In panel A I have included the descriptive statistics for 100% stock for stock mergers and takeovers. A M&A deal can be paid by stocks, cash or a mix payment including cash and stocks. In my sample there were also deals which were financed by cash, for this particular payment method I have also included the descriptive statistics (Panel B). This approach is intentionally taken, because the aim of this thesis is to show if accruals earnings management occurs in stock financed deals. It is argued in the literature (see Literature Review section) that cash financed deals doesn’t include earnings management because it is difficult to engage in earnings management with cash financed deals. In order to show the difference between stock and cash financed deals, I have included deals which were paid by cash too. The deals with part cash and part stock are also included. In appendix B I have included a correlation matrix with all the respective variables.
The total assets of both panel A and B have a higher mean than the median which suggest that there is a positive skewness. More than 50% of the observations is under the mean. Looking at ROA (t) the mean value is -14% whereas the median is -1.40%. The ROA in the cash financed deals is higher than in the stock financed deals, where the mean is 3.2% prior to the deal and a median around 4.65%. I note that stock financed deals is larger than cash financed deals. The deal size has a percentage of 0.436 for stock financed whereas cash financed has 0.065% on average.
30
31 4. Results
In this section I will presents my results regarding accruals earnings management around mergers and acquisitions. The earnings management is calculated by using the Modified Jones model (see section 3.2.1). The results are in line with previous studies regarding earnings management. Hereafter I will show the results.
4.1 Hypothesis 1
4.1.1. Main results
In order to test the first hypothesis, I have used the probit model which I discussed before. The probit model is used because the dependent variable is a dummy, it can only have value of 1 otherwise 0. The first hypothesis is tested by using the probit model where I do a probit regression of the variable stock. In order to confirm my H1, the EM coefficient should be positive and statistically significant.
32 Table 4 shows the regression calculations of probit multivariate model. Dependent variable is a dummy variable. In This model the dependent variable is a stock dummy, 1 if it is a stock financed acquisition 0 otherwise. EM t-1 is the earnings management (Modified-Jones (1991) model in the year preceding the announcement date. The Deal Size variable (Value of Transaction/Total Assetst-1). MTB t-1 is the Market to Book (Market Value/Book Value Equity) in the year preceding the deal. Cross-Industry is a dummy variable, it is 1 when cross industry (if acquiring firm operates in different industry and vice versa). The Cross-Border is a dummy variable, 1 if it is a cross-border M&A deal or 0 otherwise. The Public is a dummy variable, 1 if it is a public target firm, or 0 otherwise. ROA t-1 is Return on Assets (Net Income /Total Assets) in the year preceding the M&A deal. Leverage t-1 is the (Total Debt / Total Assets) in the year preceding the M&A deal. Year, country and industry fixed effects are included in the regression. The quantitative variables are winsorized at 1%-99%. ***/** and * is respectively given a significance level of 1%, 5% and 10%. The coefficient of EM is positive (0.0834) in cases where there is a 100% stock financed deal. For deals which were financed by 75% stocks the coefficient is 0.0923 and for 50% stock financed deals the coefficient is 0.1543 respectively.
The coefficient of EM 0.0834 means that if you increase 1 percentage point in the EM (preceding the deal) then it leads to an increase of 8% in likelihood that the deal was fully paid by stocks. So the higher this coefficient, the higher likelihood that the deal was fully paid in stocks. Furthermore, the EM coefficient is statistically significant (0.0948).
33 In order to check for robustness, I have included some fixed effects in order to test whether there are factors which could impact the M&A deals. I have confirmed with ‘Yes’ or ‘No’ if above fixed effects had any impact on the merger/takeover.
The results shown in table 4 are in line to what I expected regarding the first hypothesis. Earnings management tend to be positive and significant. Also the results are in line with previous studies (Erickson & Wang (1999); Botsari & Meeks (2008). .
The conclusion is that earnings management (discretionary accruals) is statistically significant and positive in the case of stock financed mergers/takeover. Firms managers do anticipate the deal and engage in upwards earnings management.
With the above analysis I can confirm my H1. 4.2. Hypothesis 2
In this section I will test the performance of the acquiring firms in the UK, France, Germany and The Netherlands. In this particular analysis of the long-term post performance of the acquiring firms I will include 3 years after the deal. Hereafter I will discuss the main results.
4.2.1. Main results
In this section I will test my second hypothesis where I expect that acquiring firms which engaged in accruals earnings management will have a weaker long-term performance after the deal (stock financed). In order to do this, I will use the BHAR model which is explained in chapter 3 (Research method). If the ‘DStock’ coefficient is negative then the long-term post-deal performance should be weaker.
In order finally test for the second hypothesis, the following step-by-step plan is formulated: - Step 1: BHAR regression
- Step 2: The effect of earnings management on BHAR (long-term post-deal performance) - Step 3: Final test BHAR for firms which engaged in earnings management
34
Step 1: BHAR regression
Table 5 reports the BHAR regression
Table 5 shows the results of the long-term returns post-merger performance regressions (BHAR) explained in the part 3.2.2.. from t to t+1.Dummy Stock (DStock), 1 if it is a 100% M&A deal financed by stocks, or 0 otherwise. Dummy Cash (DCash), 1 if it is a 100% M&A deal financed by cash, or 0 otherwise. LogTA -> logarithm of Total Assets. Deal Size variable is Size (Value of Transaction /Total Assets t-1). Cross-Industry is a dummy variable, it is 1 when cross industry (if acquiring firm operates in different industry and vice versa). The Cross-Border is a dummy variable, 1 if it is a cross-border M&A deal or 0 otherwise. The Public is a dummy variable, 1 if it is a public target firm, or 0 otherwise. ROA t-1 is Return on Assets (Net Income /Total Assets) in the year preceding the M&A deal. Leverage t-1 is the (Total Debt / Total Assets) in the year preceding the M&A deal. I have used fixed effects (year, country and industry) to control for any unobservable factors. These factors can influence the M&A deal. Therefore I have used cluster by year and by country-year. The quantitative variables are winsorized at 1%-99%. ***/** and * is respectively given a significance level of 1%, 5% and 10%.
Table 5 shows that deals which are financed by stock have a lower BHAR of around 18% with a statistical significance level of 1%. In order to have more solid results, I included the fixed effects year, country and industry level. Despite including the several fixed effects and clusters, my conclusions regarding the BHAR regression stays the same.
35 Table 5 shows that acquiring firms in my sample have a worse performance a year after the deal. In appendices I have included the regressions for the second and third year. The ‘DStock’ coefficient for the second year is -21% and for the third year after the deal it is -35%. Overall, the performance of the acquiring firms gets worse throughout the years. In the next step I will show the impact of earnings management on the BHAR long-term post-performance.
Step 2: The effect of earnings management on BHAR (long-term post-deal performance)
During this step I will test whether earnings management preceding the deal has influence on the estimations of BHAR in the years following the deal.
Table 6 reports the influence of EM on the BHAR
Table 6 shows the outcomes of the long-term returns post-deal performance regressions (BHAR) explained in the part 3.2.2 from t to t+1/ t+2 and t+3. I have included a Dummy EM t-1, value of 1 means that the acquiring firm engaged in earnings management prior (1 year) the M&A deal, value of 0 otherwise. ‘’LogTA’’ is explained as the logarithm of Total Assets of the acquiring firm. Deal Size variable is (Value of Transaction / Total Assetst-1). Cross-Industry is a dummy variable, it is 1 when exists cross-industry between acquirer and target. The Cross-Border is a dummy variable, 1 if it is a cross-border M&A deal or 0 otherwise. The Public is a dummy variable, 1 if it is a public target firm, or 0 otherwise. ROA t-1 is Return on Assets (Net Income /Total Assets) in the year preceding the M&A deal. Leverage t-1 is the (Total Debt / Total Assets) in the year
36 preceding the M&A deal. The quantitative variables are winsorized at 1%-99%. ***/** and * is respectively given a significance level of 1%, 5% and 10%.
The coefficient of my Dummy variable EM for the first year is -0.0411. The EM coefficient for the second year is -0.555 and for the third year -0.639. It clearly shows that earnings management has significant impact (sig. level of 5 and 10%) on the BHAR of the deals.
The significance level for the first year was held on 5% whereas for the second and third year the significant level was held on 10%. But overall, these results suggest that EM has a big role to play in the BHAR estimations.
In the next step I will perform the last test for my second hypothesis and show if earnings management leads to a weaker long-term post-deal performance of acquiring firms.
Step 3: Final test BHAR for firms which engaged in earnings management
Table 7 reports the results of the final test for the long-term post-deal performance Table 7: BHAR: EMt+1 stock financed M&A Deals
37 Table 7 shows the results of the long-term returns post-deal performance regressions (BHAR) discussed in part 3.2.2 from t to t+1/t+2 and t+3. There are two panels, Panel A and Panel B which are different. Panel A shows the results for firms which engaged in earnings management and Panel B shows results for firms who did not engage in earnings management.. The variable ‘’D EM t-1 x Stock’’ 100% is a dummy variable, value of 1 is given when the acquiring firm engaged in earnings management prior (1 year) to a 100% stock-financed M&A deal, and value 0 otherwise. The variable ‘'D NoEM t-1 x Stock 100%’’ is a dummy variable, value of 1 is given if the acquiring firm engaged in earnings management and value of 0 otherwise. LogTA -> logarithm of Total Assets. Deal Size variable is (Value of Transaction / Total Assets t-1). Cross-Industry is a dummy variable, it is 1 when the acquirer and target do not belong to the same industry, 0 otherwise. The Cross-Border is a dummy variable, 1 if it is a cross-border M&A deal or 0 otherwise. The Public is a dummy variable, 1 if it is a public target firm, or 0 otherwise. ROA t-1 is Return on Assets (Net Income /Total Assets) in the year preceding the M&A deal. Leverage t-1 is the (Total Debt / Total Assets) in the year preceding the M&A deal. The quantitative variables are winsorized at 1%-99%. ***/** and * is respectively given a significance level of 1%, 5% and 10%.
The above table 7 shows the final test for the second hypothesis which was to test if acquiring firms which engaged in earnings management had a weaker long-term performance after the merger/takeover. In order to do this I created a dummy variable which indicates 1 if it’s a stock financed merger/takeover and 0 otherwise.
The ‘DStock’ coefficient for the first year after the deal is -0.1369. The second and the third year showed a decrease in the coefficient -0.2145 and -0.3859 respectively. So this table shows that
38 acquiring firms which engaged in earnings management, suffer a lower negative post-performance in the years after the deal.
Since not all firms engaged in earnings management, I was curious how they performed after an M&A deal. In the following panel B of table 7 I show the results of the long-term post-deal performance of firms which didn’t engage in EM.
The coefficient of ‘’D NoEM Stock’ for the first year is -0.1935. I noticed that the firms that did not engage in EM have a higher negative effect on the BHAR (see first column panel A – Table 7). But in comparison with panel A of table 7, the coefficient gets lower (for the second year -0.1459 and for the third year -0.2134).
39 Panel B of table 7 shows the results for the acquiring firms which did NOT engage in upwards accruals earnings management and had a negative impact on the BHAR (only first year after the deal, year 2 and 3 were not statistically significant).
Overall, table 7 shows the final results for testing the second hypothesis. My results confirm that firms which engaged in upwards earnings management and have done a stock financed merger/takeover experience a lower BHAR in the upcoming three years after the merger/takeover. Thus, I confirm my second hypotheses and this is also consistent with the literature review.
Step 4: Conclusions
In this last step, I will highlight the main conclusions regarding the long-term post-deal acquisition performance of acquiring firms. As mentioned before, I have first done the BHAR regressions for the long-term post performance without looking at the earnings management. Secondly, I have incorporated the EM to show the influence of EM on the BHAR regressions. Finally, I have
40 included firms which engaged in EM in the test and showed that they suffer a lower long-term post-deal performance.
The first test (table 5 – first column) showed that deals which are financed by stock have a lower BHAR of around -18%. This percentage gets higher in the 2nd and 3rd year after the deal. This percentages are high because most of the acquiring firms which engaged in EM, have suffered a lower post-deal performance in the years following the M&A deal. Also the acquiring firms performed below par in the period of the Financial Crisis (2007-2008).
The second test showed that the amount of (accruals) earnings management plays a significant role in the BHAR regression. The results in table 6 (column 1) showed that the EM lowers the BHAR in the first year with -4.1% and this percentage points gets higher in the 2nd and 3rd year.
The last test I included all firms which engaged in EM and tested if their long-term post-performance was weaker in the years following the M&A deal. Table 7 showed that firms which engaged in earnings management around stock financed deals, had a BHAR of around -14% percentage points in the first year. This percentages points would increase significant in the 2nd and 3rd year.
Overall, my results regarding the test for long-term post-deal performance show that the acquiring firms in my sample have a lower BHAR in the years following the mergers and acquisition. This is in line with my expectation, thus, I confirm my H2.
41 4.3 Sensitivity analysis
In this section I will discuss the results regarding my H1 and H2 more in depth. In this section I will explain the outcome of the results and provide a link with the existing literature regarding earnings management around mergers and acquisitions. First I will analyze the results for H1 and end with a sensitivity analysis for H2.
4.3.1 Sensitivity analysis H1
In this sensitivity analysis I will discuss the results more in depth. In order to test for my
In order to test the first hypothesis, I have used the probit model which I discussed before. The probit model is used because the dependent variable is a dummy, it can only have value of 1 otherwise 0. The first hypothesis Is tested by using the probit model where I do a probit regression The outcome of this probit regression is in line with Louis (2004), Botsari & Meeks (2008) and the very first study around earnings management during M&A deals of Erickson & Wang (1999). The results of this analysis suggest that there is a statistically significant relationship between the earnings management (discretionary accruals) and stock financed deals (stock as payment method).
42 In order to check for robustness, I have included some fixed effects in order to test whether there are factors which could impact the M&A deals. The effects I have included in this check is as follows ; Year, country level and industry level respectively. In table 3 I have confirmed with ‘Yes’ or ‘No’ if above fixed effects had any impact on the merger/takeover.
Panel A of table 3 report the results from the probit regression. The following percentages are reported; 100, 75 and 50 percent. These are structured percentages and show how much % of the deal was financed with stocks.
The first column shows that if you increase 1 percentage point in the EM one year preceding the deal then it leads to an increase of at least 8% in likelihood that the deal will be fully paid by stock. The statistically significance level is 1% and the conclusion remain same with the fixed effects. Thus, the higher the EM (discretionary accruals) in a acquiring firm preceding the deal, the higher the probability that the merger/takeover is stock financed.
43 4.3.2 Sensitivity analysis H2
In this section I will discuss the test for H2 more in depth. In this section I will discuss in details whether acquiring firms which engage in EM have a weaker long-term post-deal performance. This discussion will be based on the same step-by-step plan as in paragraph 4.3.1.
Step 1: BHAR regression
In this section I will test my second hypothesis where I expect that acquiring firms which engaged in accruals earnings management will have a weaker long-term performance after the deal. In order to do this, I will use the BHAR model which is explained in chapter 3 (Research method). I have used a 4 year window starting at t (the year when the deal is announced) and t1, t2 and t3.
The BHAR regressions for testing the second hypothesis are shown in table 5. In Panel A the stock financed deals are included. It is a multivariate model whereas the dependent variable ‘DStock’ is a dummy variable. Table 5 shows that deals which are financed by stock have a lower BHAR of around 18% with a statistical significance level of 1%.
44 Looking at Table 5, it shows that acquiring firms in my sample have on average a lower 18% BHAR in first year after the deal (stock financed).
In the appendixes I have included the BHAR regression for the 2nd and 3rd year after the deal. From year t to t+2 the BHAR is around 21% with a significance level of 1%. But the BHAR for year t to t+3 gets worse and is in average around 35%. Even with using the fixed effects and clusters, there is no change in the BHAR. Overall, throughout the whole 4 year window period starting from t to t1, t2 and t3 the long-term post performance of acquiring firms in the four countries gets worse when the merger/takeover is paid by stock.
This conclusion is consistent with previous studies where Cohen en Zarowin (2010) expected a worse performance of the acquiring firms in the future. According to the paper of Cohen and Zarowin (2010) mergers and acquisition deals which are stock financed, will experience a bad performance in the future. At certain time there will be a reversal of the discretionary accruals and managers won’t be able to manipulate the earnings. According to the literature, I also expect that the acquiring firms in my sample will have a worse performance in the years after the merger/takeover.
45
Step 2: The effect of earnings management on BHAR (long-term post-deal performance)
During this step I will test whether earnings management preceding the deal influences the estimations of BHAR in the years following the deal.
Table 6 reports the influence of EM on the BHAR
I have done additional BHAR regressions for earnings management (discretionary accruals). A value of 1 is given to the dummy variable if the acquiring firms engaged in earnings management for period t+1 and 0 otherwise
46 In Table 6 the results are shown and it is clear that earnings management has a negative influence on the BHAR in the merger/takeover for the following years t+1, t+2 and t+3 (significance level of 5 and 10 %). So the results of table 6 are interpreted as follows;
Firms who engaged in earnings have on average a lower BHAR of 4,1% for t+1, 5,6% for t+2 and 6,4% for t+3. The significant level for the first and third year was 5%. The significance level for the second year was held on 10%.
But overall, these results in Table 6 suggest that EM has significant influence on the BHAR estimations.
47
Step 3: Final test BHAR for firms which engaged in earnings management
In this part I will finally do the test for the second hypothesis which was to test if acquiring firms which engaged in earnings management had a weaker long-term performance after the merger/takeover. In order to do this I created a dummy variable which indicates 1 if it’s a stock financed merger/takeover and 0 otherwise.
Table 7 reports the results of the final test for the long-term post-deal performance Table 7: BHAR: EMt+1 stock financed M&A Deals
Table 7 shows that firms which engaged in AEM and did a stock financed merger/takeover have negative influence BHAR from t to t+2 and t+3 and made a stock financed merger/takeover. To show the difference between firms which did NOT engage in AEM, I have run the same test for the BHAR. The outcome of that test is as follow;
